CMR

Model framework

CMR()	Context Maintenance and Retrieval model.
CMR.likelihood(data, group_param[, ...])	Log likelihood summed over all subjects.
CMR.fit_indiv(data, param_def[, patterns, ...])	Fit parameters to individual subjects.
CMR.generate(data, group_param[, ...])	Generate simulated data for all subjects.
CMR.record(data, group_param[, subj_param, ...])	Record model states during a simulation.
CMR.parameter_sweep(data, group_param, ...)	Simulate data with varying parameters.
CMR.parameter_recovery(data, n_sample, param_def)	Run multiple iterations of parameter recovery.

Model configuration

save_patterns(h5_file, items, **kwargs)	Write patterns and similarity matrices to hdf5.
load_patterns(h5_file[, features])	Load weights from an hdf5 file.
read_config(json_file)	Read model configuration from a JSON file.
config_loc_cmr(n_item)	Configure a localist CMR network.

Model parameters

CMRParameters()	Configuration of CMR model parameters.
CMRParameters.set_fixed(*args, **kwargs)	Set fixed parameter values.
CMRParameters.set_free(*args, **kwargs)	Set free parameter ranges.
CMRParameters.set_dependent(*args, **kwargs)	Set dependent parameters in terms of other parameters.
CMRParameters.eval_dependent(param)	Evaluate dependent parameters based on input parameters.
CMRParameters.set_dynamic(trial_type, *args, ...)	Set dynamic parameters in terms of parameters and data.
CMRParameters.eval_dynamic(param[, study, ...])	Evaluate dynamic parameters based on data fields.
CMRParameters.set_sublayers(*args, **kwargs)	Set layers and sublayers of a network.
CMRParameters.set_weights(connect, regions)	Set weights on model patterns.
CMRParameters.set_sublayer_param(layer, ...)	Set sublayer parameters.